ZikaTracking taps into the Twitter Streaming API and monitors tweets mentioning Zika-related keywords. A machine learning system trained with the supervision of experts filters informative tweets. Geographical entities mentioned in tweets - such as country and city names - are identified using the GeoNames database and used to place tweets on a global map.

The map shows events, i.e., groups of tweets that recently mentioned the same place. Blobs indicate mentioned places (not the place those tweets were posted from). Blob size relates to the frequency of recent mentions. Countries are color-coded to indicate country mentions. You can click on a place to learn more about what is going on there.

ZikaTracking monitors the Twitter global conversation to provide an awareness tool able to follow multiple events in a georeferenced context and in real time. It does not track the virus spread rather the extent of the global discussion around Zika.

ZikaTracking was designed and built by the Data Science Laboratory of the ISI Foundation (Marco Quaggiotto, André Panisson, Matteo Delfino, Ciro Cattuto, Daniela Paolotti, Michele Tizzoni) and is based on the former experience of EbolaTracking.org